Electronic devices such as cellular phones, wearable devices, tablet computers, laptops, monitors, and televisions all utilize displays in various forms and formats. Displays are generally composed of patterned arrays of pixels configured to emit light in various colors. These pixels are generally composed of organic light emitting diodes (OLEDs), liquid crystals used in combination with a backlight (e.g., LCDs), micro light emitting diodes (microLEDs), etc. Each pixel generally includes multiple subpixels that are each configured to emit specific wavelengths of light. For example, subpixels typically include red, blue, and green subpixels. These subpixels and pixels may be arranged and driven in a number of ways, with the goal of accurately reproducing an image to the human visual system. A common configuration of pixels is a RGB stripe configuration which has red, blue, and green subpixels in every pixel. In some cases, the subpixels may be subsampled, for example, an RGBG display has a green subpixel for each pixel, but only one red and one blue subpixel for two pixels.
For a variety of reasons, various compression techniques may be applied to an image that is transmitted to the display. In some cases, the compression technique utilized may result in what is termed as a “visually lossless” image being displayed by the display meaning that a typical person would not perceive any artifacts introduced by the compression technique. Some techniques, however, result in perceivable artifacts being noticeable to a user observing a display. The artifacts may include incorrect colors, blur, flickering, aliasing, blockiness, etc.
Both the display itself and any compression used may therefore introduce artifacts into an image being displayed. A number of systems have been created to test both displays and the images being provided to the displays for visual artifacts. For example, subjective test scoring using the ISO/IEC 29170-2:2017 standard procedure using human test subjects and a calibrated monitor is considered to be a highly effective way to evaluate the coding of image sequences. These subjective tests often involve a person viewing tens or hundreds of images and providing an evaluation for each one. Conducting these tests can be time consuming for both the test subjects and the test administrators. Thus, objective testing systems have been utilized to assist in evaluation.
Common objective testing systems utilize a variety of metrics to attempt to quantify visual quality, but they have not proven to be as effective as subjective test scoring. Thus common objective testing systems that use peak signal to noise ratios (PSNRs) and pattern-color sensitivity are typically used for performing preliminary testing before utilizing human test subjects. One of the issues with the objective measures is that they do not incorporate display spatial characteristics (e.g. subpixel configuration) or human perception characteristics. Thus, an improved objective testing system that takes into account display and human characteristics is needed.
The above information is only for enhancement of understanding of the background of embodiments of the present disclosure, and therefore may contain information that does not form the prior art